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What is LabelMe?
LabelMe is designed as a web-based platform that enables users to annotate images, thereby assisting in the development of image databases vital for research in the field of computer vision. Through its annotation tool, users can play an integral role in expanding this growing database. Images can be arranged into organized collections, and users have the option to create nested collections similar to traditional folder structures. When downloading their database, users will find that the arrangement of collections mirrors this folder organization. Additionally, users can upload their images to these collections and annotate them using the LabelMe tool. There are also unlisted collections that can be accessed by anyone with the specific URL, even though they remain hidden from public view. Ultimately, LabelMe strives to make both images and annotations freely available to the research community, promoting collaboration and fostering innovation. This dedication to open access underscores the significance of shared resources in propelling advancements in computer vision research, while also encouraging diverse contributions from various users.
What is Diffgram Data Labeling?
Your AI Data Platform
Top-Notch Training Data for Businesses
Data Annotation Software for Machine Learning
Enjoy a free Kubernetes Cluster for up to 3 users
RELIED ON BY 5,000 SATISFIED UBERS GLOBALLY
Images, Videos, and Text
Spatial Tools
Quadratic Curves and Cuboids, Segmentation Boxes, Polygons and Lines, Keypoints, Classification Tags, and More
You have access to the precise spatial tool you require. Each tool is user-friendly, customizable, and provides robust options for data presentation, with all tools available in Video format.
Attribute Tools
Enhanced Meaning. Greater flexibility through:
Radio buttons, Multiple selections, Date pickers, Sliders, Conditional logic, Directional vectors, and much more!
Intricate knowledge can be captured and encoded into your AI systems, facilitating deeper insights.
Streaming Data
Automation
Manual labeling can surpass automated labeling in speed by up to 10 times, significantly improving efficiency. Moreover, this rapid labeling process enhances project turnaround times, fostering quicker insights and development.
Integrations Supported
AWS CloudFormation
Amazon Web Services (AWS)
Google Cloud Platform
Kubernetes
Labelbox
Microsoft Azure
Scale GenAI Platform
TensorFlow
Integrations Supported
AWS CloudFormation
Amazon Web Services (AWS)
Google Cloud Platform
Kubernetes
Labelbox
Microsoft Azure
Scale GenAI Platform
TensorFlow
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Free
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
LabelMe
Company Website
labelme.csail.mit.edu/Release3.0/
Company Facts
Organization Name
Diffgram
Date Founded
2018
Company Location
Santa Clara CA
Company Website
www.diffgram.com
Categories and Features
Categories and Features
Data Labeling
Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management